Abstract: A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are mapped to topic clusters and the topic clusters are stored in association with the user profile. Recommendations for a user are made based on the topic clusters associated with the user'profile.

Abstract: A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are mapped to topic clusters and the topic clusters are stored in association with the user profile. Recommendations for a user are made based on the topic clusters associated with the user's profile.

Abstract: A system and method for tuning a raw mix proportioning controller used in a cement plant. A fuzzy logic supervisory controller tracks the performance of a cement plant simulator to target set points for attaining a correct mix and composition of raw materials. A genetic algorithm adjusts the fuzzy logic supervisory controller's performance by adjusting its parameters in a sequential order of significance.

Abstract: A method and system for canceling noise and compressing data from a motor phase angle sensor. In this invention, phase angle data is sampled at a first sampling rate to generate a sampled phase angle. The sampled phase angle signal is sub-sampled at a second sampling rate to generate a sub-sampled phase angle signal which is transformed by subtracting each of the sub-sampled data points of the sub-sampled signal from 90 degrees to generate a transformed signal. The transformed phase angle signal is then convoluted with a wavelet signal to generate a convoluted phase angle signal. Next, a phase angle range signal is generated by calculating the range between the largest and smallest convoluted data points within each of a plurality of segments of the convoluted signal. A moving average calculation is performed on the phase angle range signal to generate a moving average signal.

Abstract: A system and method for tuning a raw mix proportioning controller used in a cement plant. A fuzzy logic supervisory controller tracks the performance of a cement plant simulator to target set points for attaining a correct mix and composition of raw materials. A genetic algorithm adjusts the fuzzy logic supervisory controller's performance by adjusting its parameters in a sequential order of significance.

Abstract: An automatic train handling controller. In one embodiment, there is disclosed a system and method for tracking a velocity profile in a rail-based transportation system. A fuzzy logic controller is used to ensure that a train simulator complies to the velocity profile over a specified track profile while providing a smooth ride. A safety constraint enforcer is used to minimize sudden slack movements by ensuring that the control action provided by the fuzzy logic controller is kept in compliance with a set of predetermined safety constraints. In a second embodiment, there is an automatic train handling controller that smoothly manages the slack of the couplers while keeping the train within prescribed speed limits over a varying terrain.

Abstract: The invention includes a system and method for generating fulfillment value at risk scores and assessing the stability of the fulfillment value at risk scores for a portfolio of location and item pairs. The fulfillment value at risk score may be generated using fuzzy logic inference and exploratory data analysis and its stability is assessed using bootstrap algorithms.

Abstract: A system and method for diagnosing and validating a machine with waveform data generated therefrom. Historical waveform data are obtained from machines having known faults along with corresponding actions for repairing the machines and are used to develop fault classification rules. The fault classification rules are stored in a diagnostic knowledge database. The database of classification rules are used to diagnose new waveform data from a machine having an unknown fault.

Abstract: A system and method for diagnosing and validating a machine over a network using waveform data. Historical waveform data are obtained via the network from machines having known faults along with corresponding actions for repairing the machines and are used to develop fault classification rules. The fault classification rules are stored in a diagnostic knowledge database. The database of classification rules are used to diagnose new waveform data from a machine having an unknown fault, via the network.

Abstract: This disclosure describes a system and method for providing stability analysis of profitability calculations of target markets for goods or services. The system and method of this disclosure uses an internal experience database and external demographic databases. The system and method evaluates demographic data and calculates the risk associated with a variety of different goods or services. The system and method comprises a number of steps. First, a data acquisition module associates descriptor variables with different goods or services in a portfolio of goods or services. Second, a risk model module processes the various goods or services into distinct groups based upon specified characteristics. The risk model module also calculates risk values for the various goods or services and sorts the portfolio of goods or services into specified categories. Third, a profitability module calculates the net present value of each of the goods or services in the entire portfolio.

Abstract: System and method for generating a time-to-break prediction for a paper web in a paper machine. This invention uses principal components analysis, neuro-fuzzy systems and trending analysis to form a model for predicting the time-to-break of the paper web from paper mill measurements of paper machine process variables. The model is used to isolate the root cause of the predicted web break.

Abstract: A system and method for predicting web breaks in a paper machine. Principal components analysis (PCA) and classification and regression tree (CART) modeling are used to predict web break sensitivity from measurements taken from the paper mill. Also, the CART model is used to isolate the root cause of the predicted web break sensitivity.

Abstract: System and method for predicting web breaks in a paper machine. Principal components analysis and an aggregated classification and regression tree (CART) model are used to predict web break sensitivity from measurements taken from a paper mill where the paper machine is located.

Abstract: A system and method for predicting web breaks in a paper machine. Principal components analysis and an aggregated classification and regression tree (CART) model are used to predict web break sensitivity from sensor measurements taken from the paper machine.

Abstract: A system and method for predicting web breaks in a paper machine. Principal components analysis (PCA) and classification and regression tree (CART) modeling are used to predict web break sensitivity from sensor measurements taken from the paper machine. Also, the CART model is used to isolate the root cause of the predicted web break sensitivity.

Abstract: A hybrid learning system is provided for searching an experimental space. A data mart is configured to acquire, store, and manipulate a set or meta-set of data including at least historical experimental data, descriptor data, and concurrent experimental data. A search engine is designed to use unsupervised learning techniques to select a set of evaluation points representing a corresponding set of experiments to be run, based on data from the data mart. A point evaluation mechanism provided with supervised learning modules which perform predictive processing based on the evaluation points selected by the search engine, and a scoring module performs a rating operation on outputs of the learning modules to rate the outputs of the learning modules from best to worst. The data mart search engine and point evaluation mechanism allow for a repetitive processing to refine an output of potential solutions without the requirement of continually running actual physical experiments.

Abstract: A diagnostic system is provided for identifying faults in a machine (e.g., CT scanner, MRI system, x-ray apparatus) by analyzing a data file generated thereby. The diagnostic system includes a trained database containing a plurality of trained data, each trained data associated with one of plurality of known fault types. Each trained data is represented by a trained set of feature values and corresponding weight values. Once a data file is generated by the machine, a current set of feature values are extracted from the data file by performing various analyses (e.g., time domain analysis, frequency domain analysis, wavelet analysis). The current set of feature values extracted is analyzed by a fault detector which produces a candidate set of faults based on the trained set of feature values and corresponding weight values for each of the fault types. The candidate set of faults produced by the fault detector is presented to a user along with a recommend repair procedure.

Abstract: A system and method for generating a time-to-break prediction for a paper web in a paper machine. This invention uses principal components analysis, neuro-fuzzy systems and trending analysis to form a model for predicting the time-to-break of the paper web from sensor measurements of paper machine process variables. The model is used to isolate the root cause of the predicted web break.

Abstract: System and method for predicting web breaks in a paper machine. Principal components analysis and an aggregated classification and regression tree (CART) model are used to predict web break sensitivity from measurements taken from a paper mill where the paper machine is located.

Abstract: System and method for generating a time-to-break prediction for a paper web in a paper machine. This invention uses principal components analysis, neuro-fuzzy systems and trending analysis to form a model for predicting the time-to-break of the paper web from paper mill measurements of paper machine process variables. The model is used to isolate the root cause of the predicted web break.